Brain cell differences key to learning in humans and Artificial Intelligence

Researchers have found that variability between brain cells might speed up learning and improve the performance of the brain and future artificial intelligence (AI). A study found that by tweaking the electrical properties of individual cells in simulations of brain networks, the networks learned faster than simulations with identical cells. The researcher also found that the networks needed fewer of the tweaked cells to get the same results and that the method is less energy-intensive than models with identical cells & their findings could teach us about why our brains are so good at learning, and might also help us to build better artificially intelligent systems, such as digital assistants that can recognize voices and faces, or self-driving car technology. By contrast, in each cell in an artificial neural network, the technology on which AI is based is identical, with only their connectivity varying. Despite the speed at which AI technology is advancing, their neural networks do not learn as accurately or quickly as the human brain and the researchers wondered if their lack of cell variability might be a culprit. They set out to study whether emulating the brain by varying neural network cell properties could boost learning in AI. They found that the variability in the cells improved their learning and reduced energy consumption. To carry out the study, the researchers focused on tweaking the "time constant" that is, how quickly each cell decides what it wants to do based on what the cells connected to it are doing. Some cells will decide very quickly, looking only at what the connected cells have just done. Other cells will be slower to react, basing their decision on what other cells have been doing for a while. After varying the cells' time constants, they tasked the network with performing some benchmark machine learning tasks: to classify images of clothing and handwritten digits; to recognize human gestures and to identify spoken digits and commands. The results show that by allowing the network to combine slow and fast information, it was better able to solve tasks in more complicated, real-world settings.

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                                      Bedtime linked with heart health

Going to sleep between 10:00 and 11:00 pm is associated with a lower risk of developing heart disease compared to earlier or later bedtimes, according to a study. While numerous analyses have investigated the link between sleep duration and cardiovascular disease, the relationship between sleep timing and heart disease is underexplored. This study examined the association between objectively measured, rather than self-reported, sleep onset in a large sample of adults. During an average follow-up of 5.7 years, 3,172 participants (3.6%) developed cardiovascular disease. Incidence was highest in those with sleep times at midnight or later and lowest in those with sleep onset from 10:00 to 10:59 pm. The researchers analyzed the association between sleep onset and cardiovascular events after adjusting for age, sex, sleep duration, sleep irregularity (defined as varied times of going to sleep and waking up), self-reported chronotype (early bird or night owl), smoking status, body mass index, diabetes, blood pressure, blood cholesterol, and socioeconomic status. Compared to sleep onset from 10:00 to 10:59 pm, there was a 25% higher risk of cardiovascular disease with sleep onset at midnight or later, a 12% greater risk for 11:00 to 11:59 pm, and a 24% raised risk for falling asleep before 10:00 pm. In a further analysis by sex, the association with increased cardiovascular risk was stronger in women, with only sleep onset before 10:00 pm remaining significant for men. Researcher indicates that the optimum time to go to sleep is at a specific point in the body's 24-hour cycle and deviations may be detrimental to health. The riskiest time was after midnight, potentially because it may reduce the likelihood of seeing morning light, which resets the body clock. It may be that there is a sex difference in how the endocrine system responds to a disruption in circadian rhythm. Alternatively, the older age of study participants could be a confounding factor since women's cardiovascular risk increases post-menopause meaning there may be no difference in the strength of the association between women and men.

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                               Promising opportunities for treating skin fibrosis

Collagen, the main component of the skin's extracellular matrix, can cause a pathological condition if it is in excess. Applying an electric field to the skin affects collagen pathways, temporarily reducing collagen production and increasing its degradation. This is what researchers open new therapeutic perspectives for the topical treatment of skin fibrosis characterized by excessive collagen deposition. When an electric field is applied around a tumor, it "permeabilizes" the cells locally and temporarily. This permeabilization ensures, for example, the massive entry of anticancer molecules into cells and tissues, which reduces the number of doses injected into patients and limits side effects. Interestingly, physicians using this method, and for that matter, the patients themselves, have observed aesthetic and functional healing of the sites treated in this way. However, the mechanisms behind this observation had never been elucidated. A research team, used a highly sophisticated synthetic skin model, especially used to treat large burns. This artificial skin model has the advantage of being rich in the extracellular matrix, comparable to human skin in terms of composition and organization. This matrix is mainly composed of collagen, well known in cosmetics for its role in the skin's mechanical properties. Collagen, like the whole extracellular matrix, is finely regulated, in particular by its degradation by specialized enzymes which prevent it from being in excess. If this balance is disturbed, the matrix reaches a pathological or disease state, as is the case with fibrotic or hypertrophic scars, characterized by excessive collagen deposition. Using this artificial skin model, scientists have shown that applying an electric field to the skin affects many genes that influence collagen production and maturation. As soon as four hours after applying the electric field, less collagen is produced. This lasts for several days. In addition, enzymes that degrade collagen have increased activity for at least 48 hours. The application of an electric field to the skin therefore presents a great potential for future therapeutic use in the treatment of skin fibrosis.

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                                              A threat to the environment and human health

Electronic waste or e-waste is currently one of the fastest growing waste streams. This is a leading cause of environmental contamination, posing a severe threat to both the environment and human health. E-waste is a term used to describe electrical and electronic equipment of all types and its parts that have been discarded by the owner as waste. The global e-waste monitor estimated that in 2019 the quantities of e-waste was 53.6 million metric tons (Mt). This is projected to grow to 74.7 Mt by 2030. Asia generated the highest quantity of e-waste in 2019 at 24.9 Mt. It is estimated that 80 percent of e-waste from developed countries is illegally exported to low- and middle-income countries (LMICs), where labor costs and disposal are cheap, and laws are less strict or poorly enforced. A wide range of hazardous substances are emitted from e-waste including cadmium (Cd), chromium (Cr), lead (Pb), mercury (Hg), chlorofluorocarbon, polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzo-p-dioxins, and furans (PCDD/Fs). Some substances from e-waste are also economically valuable as e-waste recycling can recover valuable materials such as iron, aluminium, copper, silver and rare earth metals. Contaminants from e-waste are non-biodegradable, and can persist in the environment. They may also disturb the ecological balance of the aquatic and terrestrial environments. Humans who are living and working near e-waste recycling sites can be exposed through inhalation, ingestion, and dermal absorption if they come into physical contact with contaminated soil, dust, air, water, and food sources. Exposure to e-waste poses serious health threats, especially for vulnerable populations such as pregnant women and newborns. Numerous studies have revealed that e-waste exposures can cause toxicity in a variety of tissues, organs, and systems, such as the circulatory, respiratory, endocrine, immune, nervous, urinary, and reproductive systems. In Bangladesh, the e-waste industry is one of the fastest growing sectors. There is a lack of available information regarding the improper dismantling and processing of e-waste and its harmful effects on human and environmental health in Bangladesh. Understanding the level of environmental exposures and human health outcomes resulting from e-waste could provide an opportunity to generate strategic knowledge and may increase awareness about the effects of exposure to e-waste recycling.

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                                              Moles can be changed into melanoma

Moles and melanomas are both skin tumors that come from the same cell called melanocytes. The difference is that moles are usually harmless, while melanomas are cancerous and often deadly without treatment. A study explains how common moles and melanomas form and why moles can change into melanoma. Melanocytes are cells that give color to the skin to protect it from the sun's rays. Specific changes to the DNA sequence of melanocytes, called BRAF gene mutations, are found in over 75% of moles. The same change is also found in 50% of melanomas and is common in cancers like colon and lung. It was thought that when melanocytes only have the BRAFV600E mutation the cell stops dividing, resulting in a mole. When melanocytes have other mutations with BRAFV600E, they divide uncontrollably, turning into melanoma. This model is called "oncogene-induced senescence. Researchers discovered a new molecular mechanism that explains how moles form, how melanomas form, and why moles sometimes become melanomas. The study shows melanocytes that turn into melanoma do not need to have additional mutations but are actually affected by environmental signaling, when cells receive signals from the environment in the skin around them that give them direction. Melanocytes express genes in different environments, telling them to either divide uncontrollably or stop dividing altogether. Origins of melanoma being dependent on environmental signals gives a new outlook in prevention and treatment. It also plays a role in trying to combat melanoma by preventing and targeting genetic mutations. Researchers also expect to combat melanoma by changing the environment. These findings create a foundation for researching potential melanoma biomarkers, allowing doctors to detect cancerous changes in the blood at earlier stages. The researchers are also interested in using these data to better understand potential topical agents to reduce the risk of melanoma, delay development, or stop recurrence, and to detect melanoma early.

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